AI Solution Architect - ERP/FSM
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Key skills for this role
About the Role
Lead high-impact AI pursuits, translate AI capabilities into domain-specific outcomes, and elevate presales performance with strong technical and interpersonal skills.
Key Skills for This Role
Responsibilities
- Lead technical win pursuits for AI opportunities
- Translate AI capabilities into domain specific outcomes and architectures
- Provide insight based guidance to marketing, sales, and R&D
- Strengthen presales execution through content creation and mentoring
- Drive evolution in AI go to market model
Requirements
- Deep domain expertise in ERP, EAM, or FSM
- Strong command of IFS AI portfolio
- Experience in presales and solution engineering
- Ability to lead high impact strategic pursuits
Full Job Posting
Purpose
- As an AI Solution Architect, you work across the IFS AI portfolio, applying deep domain expertise within ERP, EAM, or FSM to win strategic deals, elevate presales performance, and drive go to market innovation.
Key Responsibilities
- Lead from the front in qualified, high impact AI pursuits by applying solution, AI portfolio, and industry depth.
- Act as the connective tissue between the AI portfolio and your domain (ERP, EAM, and/or FSM).
- Provide insight based guidance to shape marketing campaigns, sales plays, messaging, roadmap priorities, and competitive positioning.
- Strengthen presales execution through key content creation, storytelling, reusable asset development, mentoring.
- Drive evolution in our AI go to market model through cross functional collaboration.
Subject Matter Expertise
- ERP centric: Deep understanding of enterprise resource planning processes, market dynamics, and the competitive landscape.
- EAM centric: Deep understanding of enterprise asset management (EAM), APM, and AIP market dynamics.
- FSM centric: Deep understanding of field service software market dynamics.
- Multi domain: Several architects will operate credibly across two or more of these disciplines.
Success Metrics
- Contribution to AI portfolio revenue targets in partnership with sales leadership.
- Measurable improvement in presales readiness and win rates on qualified opportunities.
- Quality and reuse of solution assets, demonstrations, and proof of value engagements.
- Field sensed product feedback that fuels future AI portfolio innovation.
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